How to deal with a bulky spreadsheet that is starting to hit the limits of Excel?
Our take
Excel has long been the Swiss Army knife of data management, but as user u/EvolvedRevolution’s experience reveals, even its most advanced features can strain under the weight of complexity. Their spreadsheet—a sprawling 500,000+ formula monstrosity—struggles to keep pace with its own ambition, highlighting a critical pain point for power users: at what point does Excel transition from a capable tool to a bottleneck? The answer lies not in condemning Excel but in reimagining its role in an era where AI-native platforms can transform how we interact with data.
The problem, as outlined, is a classic case of over-engineering. A flat database import feeding into a labyrinth of nested IFs, XLOOKUPs, and array formulas creates a dependency web that slows every edit to a crawl. While array formulas and LET functions can optimize calculations, their cascading effects in such a structure may do more harm than good—and VBA, though powerful, demands expertise many users lack. This mirrors the broader challenge articulated in *Slow Spreadsheet - Need Troubleshooting*, where legacy systems crumble under modern demands. Excel’s strength has always been flexibility, but its lack of built-in automation for dynamic workflows leaves users like u/EvolvedRevolution fighting fires in a spreadsheet designed for a different era.
Yet the real story here isn’t just about speed—it’s about the future of data management. As noted in our recent analysis of AI-driven tools, the next frontier lies in platforms that merge Excel’s familiarity with intelligent automation. Imagine a system where formulas self-optimize, dependencies update frictionlessly, and manual enrichment integrates seamlessly with AI-driven insights. This isn’t a rejection of Excel; it’s an evolution. Tools like those discussed in *Excel Templates for Statistics Displaying Incomplete Answers* show how structured frameworks can streamline complexity—principles applicable far beyond academia.
For users like u/EvolvedRevolution, the path forward may involve hybrid solutions. While mastering VBA could yield short-term gains, the long-term answer likely resides in adopting platforms that abstract away dependency management and formula overhead. The key is preserving the human-centered ethos that makes spreadsheets indispensable while leveraging technology to amplify—not replace—human expertise. As AI-native tools mature, the question isn’t whether Excel will become obsolete, but how it will adapt to remain the hub of innovation in data workflows. The future belongs to systems that empower users to focus on analysis, not maintenance—a future we’re only beginning to unlock.
Hello all,
I have been venturing on quite the Excel journey the past year or so. I made a corporate spreadsheet that is approaching 500k formulas and that is starting to get serious speed issues at this point. It is 2026, so I conversed with ChatGPT several times regarding the speed issue, but realized I am way better off asking the experts here anyways.
What is the problem
So, my spreadsheet imports flat databases with specific information regarding objects that need further analysing. The imported flat databases run from say A tot CC or something, from which I probably draw about 12-15 datafields that are used for further analysis. It 'may' be more in the future. Afterwards, said data gets 'enriched' (manually) by things that aren't in the database, also because said data needs a human eye that cannot be automated. So far, so good.
Right now, each object gets analysed from several different angles. As it stands, my spreadsheet runs from A until NA or something on the Formula Page. Many columns receive data from preceding columns, that are in the turn the result of many (slightly complex) logical IF or IFS tests, many of which are nested 3 or 4 deep. Often, they work in conjunction with X.LOOKUP to retrieve values, as the columns on the formula page are not equal.
For example: A until BC on the Formula Page may analyze 150 objects, BD until DD may analyse 100 objects (from the same dataset, so narrower), and so forths. Thus a lot of X.LOOKUP is required, also because the first 'block' comes up with values that need to be found with X.LOOKUP. Also, values need to be retrieved from the flat database 'import' page with X.LOOKUP. Finally, X.LOOKUP is an insurance compared to FILTER, as I am not fully convinced that empty values in the flat database always contain a space (" ").
To get to the point
I use many IF, IFS, AND, and if need be, OR, formulas. Thinks: tens of thousands, probably in excess of 100k.
These are compounded with X.LOOKUP, or X.LOOKUP gets used copiously without those. Here too, think tens of thousands.
These formulas are - as much as possible - in array format, even though I find it controversial to do that as I consider how it can create a chain of updates throughout the spreadsheet.
'Dependencies' is the name of the game, with one object receiving many possible alterations / adjustments due to manual input data, for which the spreadsheet needs to provide.
Right now, when I update a value, it may take up to 4 seconds to update the spreadsheet, which is already beyond the annoyance point for me. This leads me to these (hopefully) simple questions:
Is it smart to use array formulas, knowing that each thing I change should only impact that one object line (for example, row 488) and none other? It is important to mention that object 1 does not influence object 488, or any other. Any manual data field only effects the object in the row it is in. In my mind, array formulas do not make sense in that regard, as it can result in a cascade of updates, but apparantly array formulas are 'way more efficient'.
Is use of a VBA library the way to go to reduce lag and create more of an instant spreadsheet again? I am not able to code in VBA yet, but I am in the slow process of learning it regardless.
Alternatively: should I use LET whenever a repeated lookup is needed in the same formula?
Really looking for to your answers!
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